<abstract xmlns="http://www.w3.org/1999/xhtml">In December 2019 a virus named COVID-19 appeared in China, precisely in the city of Wuhan. This virus was declared a global pandemic by the World Health Organization in March 2020. Since no adequate medical treatment has yet been discovered for this virus, many world institutions are committed to share with each other the data they collect and process in their laboratories. A large amount of these data is shared with citizens in order to inform about the risk that threaten us by virus COVID-19.Various credible world institutions such as the World Health Organization (WHO), Johns Hopkins University (JHU), the European Centre for Disease Prevention and Control (ECDC), etc., are providing various statistical data to address the issues raised by this emergent situation, but these reports in some cases are putting doubts on the completeness and the transparency of the data, which are not sufficiently processed and which then create confusion about the risks that we are facing.In this paper we are conducting a study of the quality of current global datasets from the must credible sources related to COVID-19. Also, we are comparing datasets collected from Republic of Kosovo and Republic of North Macedonia with corresponding data from WHO, ECDC and JHU datasets.To analyze datasets from different sources, we are using Power BI tool, making the improvement through the implementation of adequate dimensions and methods of improving the quality of datasets.</abstract>

In December 2019 a virus named COVID-19 appeared in China, precisely in the city of Wuhan. This virus was declared a global pandemic by the World Health Organization in March 2020. Since no adequate medical treatment has yet been discovered for this virus, many world institutions are committed to share with each other the data they collect and process in their laboratories. A large amount of these data is shared with citizens in order to inform about the risk that threaten us by virus COVID-19.Various credible world institutions such as the World Health Organization (WHO), Johns Hopkins University (JHU), the European Centre for Disease Prevention and Control (ECDC), etc., are providing various statistical data to address the issues raised by this emergent situation, but these reports in some cases are putting doubts on the completeness and the transparency of the data, which are not sufficiently processed and which then create confusion about the risks that we are facing.In this paper we are conducting a study of the quality of current global datasets from the must credible sources related to COVID-19. Also, we are comparing datasets collected from Republic of Kosovo and Republic of North Macedonia with corresponding data from WHO, ECDC and JHU datasets.To analyze datasets from different sources, we are using Power BI tool, making the improvement through the implementation of adequate dimensions and methods of improving the quality of datasets.

A Study on Comparative Analysis of COVID-19 Datasets

Faculty of Contemporary Sciences and Technologies

Faculty of Electrical and Computer Engineering

University of Prishtina “Hasan Prishtina”

SEEU Review

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"A Study on Comparative Analysis of COVID-19 Datasets"}

In December 2019 a virus named COVID-19 appeared in China, precisely in the city of Wuhan. This virus was declared a global pandemic by the World Health...

A Study on Comparative Analysis of COVID-19 Datasets

Online veröffentlicht: 16. Dez. 2020

Seitenbereich: 104 - 120

DOI: https://doi.org/10.2478/seeur-2020-0007

Schlüsselwörter
COVID-19, Datasets, Data Dimensions, Open Data

© 2020 Genc Hamzaj et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

A Study on Comparative Analysis of COVID-19 Datasets

Online veröffentlicht: 16. Dez. 2020

Seitenbereich: 104 - 120

DOI: https://doi.org/10.2478/seeur-2020-0007

SchlüsselwörterCOVID-19, Datasets, Data Dimensions, Open Data

© 2020 Genc Hamzaj et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
COVID-19, Datasets, Data Dimensions, Open Data